Coded distributed computing was recently introduced to mitigate the effect of stragglers on distributed computing. This paper combines ideas of approximate computing with coded computing to further accelerate computation. We propose successive approximation coding (SAC) techniques that realize a tradeoff between accuracy and speed, allowing the distributed computing system to produce approximations that increase in accuracy over time. If a sufficient number of compute nodes finish their tasks, SAC exactly recovers the desired computation. We theoretically provide design guidelines for our SAC techniques, and numerically show that SAC achieves a better accuracy-speed tradeoff in comparison with previous methods.

翻译：代码分布式计算是最近引入的,目的是减轻散装计算中散装计算者的影响。本文将近似计算和编码计算相结合,以进一步加速计算。我们提出连续近似编码技术,在精确度和速度之间实现权衡,使分布式计算系统产生近似,从而随着时间的推移提高准确度。如果有足够数量的计算节点完成它们的任务,那么SAC就完全回收了预期的计算。我们从理论上为我们的 SAC 技术提供了设计指南,并用数字显示SAC比以前的方法实现了更好的准确率和速度的权衡。